Understanding the basis for individual sensitivity to triggers of innate immunity is inhibited by the inability to interpret multivariate changes in quantitative signaling parameters that are related to Toll-like receptor signaling. Thus there is urgent need for multidisciplinary approaches to assess and interpret variability in Toll-like receptor signaling in terms of its impact on susceptibility to infectious agents. Our long-term goal is to improve the clinical management of infectious diseases by establishing the scientific foundation for a prognostic technology to aid in the rational design of therapeutic strategies tailored to individual patients. Thus, the proposed research is relevant to that part of NIH's mission that pertains to developing fundamental knowledge that will potentially help to reduce the burdens of human disability. The overall objective of this R21 application is to identify unique patterns of signaling proteins associated with sensitivity to infectious agents and to apply the computational tools of reaction pathway analysis to interpret the significant of these patterns of protein expression. Our central hypothesis is that dendritic cells derived from different inbred mouse strains exhibit heterogeneity in response to a cell membrane component of gram-negative bacteria. Furthermore, this heterogeneity is due to variations in expression of proteins that comprise the Toll-like receptor 4 (TLR4) signaling pathway. The rationale that underlies proposing this research as an R21 is that we expect to remove the risk of potential failure that would otherwise exist at the R01 level by establishing that dynamic differences in TLR4 signaling among inbred mouse strains is measurable and can be interpreted using reaction pathway analysis. To test this hypothesis, we will pursue two specific aims: 1) Establish that dynamic differences in cellular response to LPS exist within genetic variants of a species;and 2) Establish how reaction pathway analysis can be used to interpret differential patterns of protein expression within cellular signaling networks. Under the first aim, our working hypothesis is that cells that are phenotypically similar, as represented by dendritic cells derived from two different inbred mouse strains, exhibit variations in expression of proteins involved in TLR4 signaling that confer differential sensitivity to lipopolysaccharide (LPS). Under the second aim, our working hypothesis is that an algorithm for the computer-assisted assembly of reaction mechanisms can be used to create an unbiased model of the early signaling events in the TLR4 signaling network. This model can be used to interpret how differences in protein expression influence the cellular response to LPS. The proposed research is innovative as it provides a novel approach that combines cutting-edge techniques in computational systems biology and polychromatic flow cytometry to address the pressing issue of understanding the mechanistic basis for susceptibility to infectious disease.